Mapping mosquito larval densities and assessing area vulnerable to diseases transmission in Nile valley of Giza, Egypt

Diversity and abundance of mosquito larvae have significant impact on the dynamics of disease transmission. In the present study, remote sensing (RS) technology integrated with field survey and spatial analyses were utilized to map mosquito breeding habitats and assess areas vulnerable to disease tr...

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Main Authors: Alaa Nagy, Ahmed El-Zeiny, Mohamed Sowilem, Wedad Atwa, Manal Elshaier
Format: Article
Language:English
Published: Elsevier 2022-02-01
Series:Egyptian Journal of Remote Sensing and Space Sciences
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1110982321001125
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author Alaa Nagy
Ahmed El-Zeiny
Mohamed Sowilem
Wedad Atwa
Manal Elshaier
author_facet Alaa Nagy
Ahmed El-Zeiny
Mohamed Sowilem
Wedad Atwa
Manal Elshaier
author_sort Alaa Nagy
collection DOAJ
description Diversity and abundance of mosquito larvae have significant impact on the dynamics of disease transmission. In the present study, remote sensing (RS) technology integrated with field survey and spatial analyses were utilized to map mosquito breeding habitats and assess areas vulnerable to disease transmission in the Nile Valley of Giza governorate. An entomological survey was carried out to 20 accessible breeding sites at the study area during the period 6th–9th December 2019. Mosquito larvae were collected and transferred to the laboratory for density calculation and species identifications. A calibrated Landsat OLI image was processed to produce Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-Up Index (NDBI), Normalized Difference Moisture Index (NDMI), Normalized Difference Water Index (NDWI), Normalized Difference Salinity Index (NDSI), and Land Surface Temperature (LST). Results revealed that Culex pipiens was the most dominant species in the study region with a total percentage of 95.04%. High density of mosquito larvae was characterized by NDVI 0.12 to 0.39, NDBI − 0.20 to 0.05, NDMI − 0.05 to 0.20, NDWI − 0.34 to − 0.10, NDSI − 0.39 to − 0.12, and LST 19.30 to 24.82 ℃ which represents the optimal conditions for mosquito breeding. It could be concluded that Giza region, particularly Agouza, Kerdasa, Dokki, Bulaq Dakror and Omrania, is highly affected by Cx. pipiens, with a high potentiality of filariasis disease transmission.
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spelling doaj.art-aa503e35b4e448df896362a66be2fd8a2022-12-21T18:12:29ZengElsevierEgyptian Journal of Remote Sensing and Space Sciences1110-98232022-02-012516371Mapping mosquito larval densities and assessing area vulnerable to diseases transmission in Nile valley of Giza, EgyptAlaa Nagy0Ahmed El-Zeiny1Mohamed Sowilem2Wedad Atwa3Manal Elshaier4Department of Zoology and Entomology, Faculty of Science (Girls Branch), Al-Azhar University, Cairo, Egypt; Corresponding author.Department of Environmental Studies, National Authority for Remote Sensing and Space Sciences (NARSS), Cairo, EgyptDepartment of Environmental Studies, National Authority for Remote Sensing and Space Sciences (NARSS), Cairo, EgyptDepartment of Zoology and Entomology, Faculty of Science (Girls Branch), Al-Azhar University, Cairo, EgyptDepartment of Zoology and Entomology, Faculty of Science (Girls Branch), Al-Azhar University, Cairo, EgyptDiversity and abundance of mosquito larvae have significant impact on the dynamics of disease transmission. In the present study, remote sensing (RS) technology integrated with field survey and spatial analyses were utilized to map mosquito breeding habitats and assess areas vulnerable to disease transmission in the Nile Valley of Giza governorate. An entomological survey was carried out to 20 accessible breeding sites at the study area during the period 6th–9th December 2019. Mosquito larvae were collected and transferred to the laboratory for density calculation and species identifications. A calibrated Landsat OLI image was processed to produce Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-Up Index (NDBI), Normalized Difference Moisture Index (NDMI), Normalized Difference Water Index (NDWI), Normalized Difference Salinity Index (NDSI), and Land Surface Temperature (LST). Results revealed that Culex pipiens was the most dominant species in the study region with a total percentage of 95.04%. High density of mosquito larvae was characterized by NDVI 0.12 to 0.39, NDBI − 0.20 to 0.05, NDMI − 0.05 to 0.20, NDWI − 0.34 to − 0.10, NDSI − 0.39 to − 0.12, and LST 19.30 to 24.82 ℃ which represents the optimal conditions for mosquito breeding. It could be concluded that Giza region, particularly Agouza, Kerdasa, Dokki, Bulaq Dakror and Omrania, is highly affected by Cx. pipiens, with a high potentiality of filariasis disease transmission.http://www.sciencedirect.com/science/article/pii/S1110982321001125MosquitoEnvironmental characterizationRemote sensingGiza governorate
spellingShingle Alaa Nagy
Ahmed El-Zeiny
Mohamed Sowilem
Wedad Atwa
Manal Elshaier
Mapping mosquito larval densities and assessing area vulnerable to diseases transmission in Nile valley of Giza, Egypt
Egyptian Journal of Remote Sensing and Space Sciences
Mosquito
Environmental characterization
Remote sensing
Giza governorate
title Mapping mosquito larval densities and assessing area vulnerable to diseases transmission in Nile valley of Giza, Egypt
title_full Mapping mosquito larval densities and assessing area vulnerable to diseases transmission in Nile valley of Giza, Egypt
title_fullStr Mapping mosquito larval densities and assessing area vulnerable to diseases transmission in Nile valley of Giza, Egypt
title_full_unstemmed Mapping mosquito larval densities and assessing area vulnerable to diseases transmission in Nile valley of Giza, Egypt
title_short Mapping mosquito larval densities and assessing area vulnerable to diseases transmission in Nile valley of Giza, Egypt
title_sort mapping mosquito larval densities and assessing area vulnerable to diseases transmission in nile valley of giza egypt
topic Mosquito
Environmental characterization
Remote sensing
Giza governorate
url http://www.sciencedirect.com/science/article/pii/S1110982321001125
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